Dr. Christina Ramsenthaler

Professor

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Biography

Christina Ramsenthaler is a professor at the ZHAW Zurich University of Applied Sciences, specializing in methodology and methods in nursing science. She leads various SENIORS projects and is responsible for several courses in quantitative methods as part of the MSc Nursing program. Her research interests include statistical models, particularly using R, and she is involved in joint PhD programs with the University Hospital Zurich and the University of Zurich. Christina has extensive teaching experience and has held positions in several prestigious institutions, including the Wolfson Palliative Care Research Centre at the University of Hull and the Cicely Saunders Institute at King's College London. Her academic background includes a PhD in Palliative Care from King's College London, as well as multiple professional certificates in related fields. She has also worked in various roles in palliative medicine and social sciences research institutions in Germany.

Research Interests

Experience

Professor

2020-03-01 — Present

ZHAW Zurich University of Applied Sciences • Winterthur, Switzerland

Professor in methodology and methods, leading SENIORS projects.

Visiting Scholar

2017-01-01 — Present

Cicely Saunders Institute, King's College London • London, UK

Engaged in research methods and statistics in palliative care.

Academic Staff

2020-12-01 — 2021-09-01

University Hospital Freiburg, Germany • Freiburg, Germany

Worked in the Department of Palliative Medicine.

Postdoctoral Researcher

2017-04-01 — 2018-02-01

GESIS-Leibniz Institute for the Social Sciences • Mannheim, Germany

Conducted research in social sciences.

Requirements for ZHAW Zurich University of Applied Sciences

Master Program
Requirements
GPA Requirement
Required:3
TOEFL
Listening
Required:20
Reading
Required:20
Writing
Required:20
Speaking
Required:20
Total
Required:83
IELTS
Listening
Required:5.5
Reading
Required:5.5
Writing
Required:5.5
Speaking
Required:5.5
Overall
Required:5.5
Duolingo
Overall Score
Required:115
Overall
Required:115
Prerequisites
Bachelor's degree in a relevant technical or engineering field Letter of recommendation from a university lecturer
Application Checklist
  • Bachelor's degree certificate and transcripts
  • Curriculum Vitae (CV)
  • Motivation letter
  • Passport or ID card copy
  • Passport photo (JPG format)
  • Proof of English proficiency
Specialization Notes

This requirement applies generally to the Master of Science in Engineering and its specializations like Data Science, Computer Science, and Medical Physics.